Azcorra Et Al Intergenerational Influences on Maya

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Intergenerational influences on the growth of Maya

children: The effect of living conditions experienced by mothers and maternal grandmothers during their childhood

Journal: American Journal of Human Biology

Manuscript ID: Draft

Wiley - Manuscript type: Original Research Article

Date Submitted by the Author: n/a

Complete List of Authors: Azcorra, Hugo; Centro de Investigación y de Estudios Avanzados del Instituto Politecnico Nacional, Departamento de Ecología Humana Dickinson, Federico; Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Departamento de Ecología Humana Bogin, Barry; Loughborough University, Human Sciences Rodriguez, Luis; Universidad Autonoma de Yucatan, Facultad de Matematicas Varela-Silva, Maria; Loughborough University, Human Sciences

Keywords: Maya, Yucatán, Growth, Intergenerational influences

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American Journal of Human Biology

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Intergenerational influences on the growth of Maya children: The effect of living

conditions experienced by mothers and maternal grandmothers during their

childhood

Hugo Azcorra1§, Federico Dickinson1, Barry Bogin2, Luis Rodríguez3, and Maria

Inês Varela-Silva2.

1: Departamento de Ecología Humana, Centro de Investigación y de Estudios

Avanzados del Instituto Politécnico Nacional (Cinvestav)-Unidad Mérida, 97310

Mérida, Yucatán, México; 2: Centre for Global Health and Human Development,

School of Sports, Exercise and Health Sciences, Loughborough University,

Loughborough, LE11 3TU United Kingdom; 3: Facultad de Matemáticas,

Universidad Autónoma de Yucatán, Mérida, Yucatán, México; §: corresponding

author.

[email protected]

This research was funded by the National Council of Science and Technology

of Mexico (Conacyt grant no. 168047)

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ABSTRACT

Objectives To test the hypothesis that living conditions experienced by

maternal grandmothers (F1 generation) and mothers (F2 generation) during their

childhood are related to height and leg length (LL: height – sitting height) of their

6-to-8 year old children (F3 generation). Methods From September 2011-June

2012 we obtained height and LL, and calculated z-scores values of these

measurements for all participants who are Maya living in Merida, Yucatan,

Mexico. Several socioeconomic parameters of maternal and grand-maternal

living conditions during childhood were examined. Multiple regression models

were adjusted to examine the relation of anthropometric and intergenerational

socioeconomic parameters of F1 and F2 with the z-score values of height and LL

of children. Results Children´s height and LL were positively predicted by the

height and LL of mothers, respectively, with LL influenced relatively more than

height. None of the mothers’ SES variables were significant. Grandmothers who

lived during their own childhood in transitional housing built with perishable

materials predicted significant reductions in children´s height and LL,

suggesting relevant intergenerational effects of household environment.

Grandmothers who lived in bigger families predicted significantly greater height

and LL in their grandchildren. Conclusions Our findings support the hypothesis

that living conditions experienced by maternal grandmothers during their growth

period influence the growth of their children and grandchildren. Results suggest

that LL is more sensitive to intergenerational influences than is total height and

that the transition from a traditional rural lifestyle to urban conditions results in

new exposures for risk in human physical growth.

Key words: Maya, Yucatan, growth, intergenerational influences.

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INTRODUCTION

The process of growth is a complex phenomenon strongly influenced by the

social, economic and political conditions surrounding the group (Bogin and

Loucky, 1997; Steckel, 2012; Stinson, 2012). It has been suggested that the

current biological status of a group can also be explained by ecological

conditions experienced by recent ancestors during their growth period. In 1986,

Irving Emanuel defined the intergenerational influences hypothesis (IIH) as

“those factors, conditions, exposures and environments experienced by one

generation that relate to the health, growth and development of the next

generation” (Emanuel, 1986, p 27). Subsequent theoretical contributions

suggest that growth trajectories of children are also influenced by factors that

trace the nutritional history of matrilineal ancestors, including their nutrition

during prenatal stage and first years of postnatal life (Kuzawa, 2005).

Most of the accumulated evidence of intergenerational influences on

growth is on the prenatal stage (Emanuel, 1986; Ounsted et al., 1986; Klebanoff

and Yip, 1987; Emanuel et al., 1992; Emanuel et al., 1999; Emmanuel et al.,

2004; Hypponen et al., 2004; Martin et al., 2004; Kuzawa, 2005; Jasienska,

2009; Alwasel et al., 2011; Alwasel et al., 2013). The intergenerational effects

on postnatal growth have been less studied. Some studies provide results about

the association between parental and offspring height. Correlation coefficients

show that associations between mothers and offspring are stronger than

associations between fathers and offspring in all ages (Alberman, 1991;

Hypponen et al., 2004; Ghosh and Malik, 2007; Gray et al., 2012). However,

parent-offspring correlations reflect both the effect of genes and shared

environmental factors such as diet and life style (Towne et al., 2012).

The Maya are one of the largest and most important ethnic groups in

Mesoamerica (Thompson, 1973). Merida, the capital city of the Yucatan state,

in Mexico, is the home of a great number of Maya people resident in poor

neighbourhoods (Lizama, 2012). Historically, the Maya from Yucatan have lived

under very unfavourable socioeconomic conditions (Bracamonte, 2007), and

continue to do so (Azcorra et al., 2013; Wilson et al., 2013). This has impacted

negatively the biosocial status of the Maya. Previous studies show that Maya

from Yucatan exhibit high rates of undernutrition (mainly short stature) during

the growing period (Kelley, 1991; Wolanski et al., 1993; Siniarska and Wolanski,

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1999; Azcorra et al., 2009; Varela-Silva et al., 2009; Varela-Silva et al., 2012),

and in adulthood. Despite overall improvements of social and economic

conditions since the end of the colonial period in Mexico (1821) research

indicates the absence of a positive secular change in stature for the Maya

people (McCollough, 1982; Siniarska and Wolanski, 1999).

In a previous article we described the nutritional status of a sample of

109 triads of Maya children, their mothers, and maternal grandmothers from

Merida, Mexico (Azcorra et al., 2013). We confirmed the hypothesis that leg

length-relative-to-stature is a more sensitive indicator of nutrition and health

than is total height or sitting height. In that study the analysis was based on the

examination of correlations between grandmothers and children and mothers

and children. In the present study we extend the analysis with a bio-cultural

model to test the IIH and ascertain the impact of biosocial background of urban

Maya grandmothers (F1 generation) and mothers (F2 generation) on the linear

growth and nutritional status of their children (F3 generation). This study

contributes to the knowledge about the intergenerational influences on postnatal

growth in groups with a long adverse socioeconomic history.

METHODS

From September 2011 to June 2012 a cross-sectional study was undertaken on

a sample of 109 triads of urban Maya children (6-to-8 year old), their mothers

and their maternal grandmothers from the city of Merida. The number of triads

needed for the study was obtained through a power analysis calculation. Maya

surnames were used as a proxy for Maya ancestry; the requirement for

inclusion in the sample was that children, mothers and grandmothers had to

have at least maternal Maya surname. Schools (n = 20) where recruitment was

made were randomly selected from the south of Mérida, where Maya language

speakers and people with the lowest level of income are concentrated. To allow

for maximum geographic and socioeconomic variability in the sample, we

selected no more than 10 children from each school. More details of sample

size calculation and recruitment process of participants are described by

Azcorra et al (2013).

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Measurements We only focused, in this study, on height and sitting height of

the participants. Leg length (LL) was calculated by subtracting sitting height

from height. Height and LL were transformed to z-score values using the

Comprehensive references published by Frisancho (2008). Particularly in the

case of mothers and grandmothers, z-score values were useful to

accommodate the effect of loss of height with age. Additionally, grandmothers

were classified as short stature when their height-for-age was below 5th

percentile of the reference, which for this sample corresponded to less than 150

cm. We focused on the intergenerational effects on the height and LL of

children because these measurements provide information about the nutritional

history of individuals (Bogin & Keep, 1999; Bogin & Varela-Silva, 2010), and are

related to the risk for adult mortality (Barker et al., 1990; Leon et al., 1995) and

health outcomes at adulthood such as obesity, insulin resistance, type 2

diabetes and heart diseases (Forsen et al., 2000; Lopez-Alvarenga et al., 2003;

Asao et al., 2006).

The biosocial background of mothers and grandmothers was analyzed

through 1) current anthropometric characteristics: height and LL (z-score

values) and, 2) socioeconomic indicators experienced during childhood.

Children were measured at schools and adult women at homes, all of

them by trained personal. Anthropometric measurements were taken following

standardized methods (Lohman et al., 1988).

Home visits were used to apply socioeconomic questionnaires to

mothers and grandmothers. Data on socioeconomic conditions experienced

during maternal and grand-maternal childhood were obtained through the same

questions. Some questions examined the general living conditions: place of

birth and growing up, family size, number of siblings, number of rooms used to

sleep, type of water to drink, availability of toilet at home, construction materials

of the house, household assets, parents’ occupation and work during childhood.

Other questions examined some conditions experienced by mothers and

grandmothers, such as: serious illness or death of parents, divorce or

separation of parents, job loss of parents and alcoholism in the immediate

family. Mothers and grandmothers were interviewed separately. In some cases

the assistance of the mothers was requested when grandmothers did not

understand the questions because they did not speak Spanish fluently.

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Three categories of maternal and grand-maternal house type were

defined according to the materials of construction: 1) traditional Maya rural type

(dirt floor, palm leaf ceilings and wattle and daub walls), 2) perishable materials

(dirt or cement floor, cardboard or metal sheets for walls and ceilings) and, 3)

durable materials (cement floor and cement blocks in walls and ceilings).

Ethical concerns The research was approved by the Bioethics Committee for

the Study of Human Beings of the Center for Research and Advanced Studies

of the National Poly- technic Institute of Merida, Mexico and by the

Loughborough University Advisory Ethical Committee. The mothers and

grandmothers signed consent forms for themselves and mothers on behalf of

their children. Those grandmothers who could not sign their name were asked

to provide their fingerprints as proof of consent. For ethical reasons, adult

women were measured only by women of the research team. All children

provided us verbal consent to be measured.

STATISTICAL ANALYSIS

Intergenerational influences of grandmothers and mothers on children’s growth

status were assessed through multiple regression models. Several models were

adjusted for the outcome variables of z-height and z-LL. Outcome variables

were normally distributed. Model building was done following an exploratory

approach. In order to decide which variables should be included in the final

models each predictor variable was regressed against each outcome variable.

The variables that showed a significant coefficient (p<0.05) were retained in the

model.

We consistently found that paternal job loss during maternal childhood,

grand-maternal home index and family size during childhood predicted the z-

height and z-LL of children and this result did not change with the inclusion of

any other independent variable in the model. For each analysis, model 1

included only the maternal stature or LL as predictors. In model 2 the variable

paternal job loss during childhood (0 = No, 1 = Yes) was added. In model 3,

three grand-maternal intergenerational predictors were added: 1) short stature

(0 = No, 1 = Yes), 2) home type (0 = Maya type, 1= perishable materials, 2 =

durable materials) and, 3) family size (continuous).

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The validity of the final models was assessed through several diagnostic

tests. All models met the assumptions for multiple regression model building.

Particular interest was given to collinearity between predictors included in the

models; variance inflation factor (VIF) values informed us that no cases violated

this assumption. Additionally, residuals of the models were normally distributed

and all predictors had linear relationships with outcomes. In all analyses, the

significance level was set at α = 0.05.

RESULTS

Nutritional status of participants has been described recently by Azcorra et al.

(2013). Short stature in adult women and stunting and short LL in children were

defined when height-for-age and LL-for-age were below the 5th percentile of the

Frisancho Comprehensive references (Frisancho, 2008). Mothers and

grandmothers exhibited very low heights (means of 147.91 cm [SD = 4.84] and

143.08 cm [SD = 4.77], respectively) and 71% and 90% of them were classified

as short stature. Stunting in children, defined as z-height less than -1.650 of the

reference, was present in 11% of the sample. The prevalence short LL, defined

as z-LL less than -1.650 was 29%.

Intergenerational influences The models of intergenerational influences on

children’s height and LL are shown in Tables 1 and 2. Maternal z-score for

height and LL positively predicted children’s growth in all models. Paternal job

loss during maternal childhood did not predict significantly the growth of

children. The presence of short stature in grandmothers did not predict

significantly the outcome variables. Grand-maternal home type significantly

impacted the growth of children. Those grandmothers who lived during their

childhood in a household built with perishable materials predicted a decrease in

their grandchildren’s z-score for height and LL in comparison to children whose

grandmothers lived in a traditional rural type house. For LL we also found that

grandmothers who lived in a house built with durable materials positively

impacted the growth of the children, but this effect was marginally significant (P

= 0.059). Greater grand-maternal family size during childhood positively

predicted the children´s LL. The inclusion of grand-maternal predictors

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contributed to the increase of the explained variance for height by 8% and for

LL by 16%.

PLEASE INSERT TABLE 1 HERE

PLEASE INSERT TABLE 2 HERE

DISCUSSION

Our results suggest that living conditions experienced by mothers and

grandmothers during childhood contribute to shape the linear growth status of

children of F3 generation. We developed our regression models based on our

previous findings (Azcorra et al. 2013) of significant correlations between child-

mother and mother-grandmother dyads in height, sitting height and LL, but not

between child-grandmother dyads. Accordingly, in the present analysis we

included first the maternal intergenerational predictors in models 1 and 2, and

then grand-maternal predictors in model 3.

Our previous analyses and our current multiple regression models

showed that children’s height and LL were positively predicted by maternal

height and LL respectively, and this effect did not change after the inclusion of

grand-maternal anthropometric and socioeconomic factors. We recognize that

genetic factors cannot be ignored in the context of our results. However two

relevant considerations should be pointed out: 1) recent evidence suggests that

while many genes influence the linear growth of our species, the variance in

height explained by the genome accounts for only a small proportion (currently

estimated at less than 10%) of the total variance of a given trait (Mortier and

Vandem Berghe, 2012), and 2) the expression of the genomic regulation of

growth in height tends to be lower in populations under disadvantaged living

conditions (Mueller 1976, Lauderdale and Rathouz, 1999; Silventoinen et al.,

2000). For instance, reviewing 24 studies of parent-child correlations, Mueller

(1976) found that the genetic component of such correlations tends to be low in

developing countries, in which the presence of several environmental factors

tend to induce variation in growth and reduce the phenotypical expression of

genes. The United States-born children of Guatemalan Maya immigrant parents

were found to be 11.5 cm taller, on average, and have longer legs, averaging

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6.8 cm longer than Guatemala-living Maya children of the same ages (5-12

years old, Bogin et al., 2002). The Maya-American children had body

proportions more like those of European-American children in the US than like

Maya children in Guatemala. Improvements in the environment for growth, in

terms of nutrition and health, seemed to explain both the trends in greater

stature and relatively longer legs for the Maya-Americans. Gene-environment

interaction seems to be more relevant in growth than only genes per se,

particularly in those populations exposed to chronic stress.

The intergenerational influences hypothesis (IIH) has been previously

tested by Varela-Silva et al (2009) in a sample of 206 Maya children (120 girls)

4-6 years of age and their mothers living in the south of Merida. In that study it

was found that Maya children whose mothers’ height was below 150 cm were

3.6 times more likely to be stunted than children whose mothers’ height was

above 150 cm. In addition, children with birth weights below 3,000 g were over

three times more likely to be stunted than children within the range of normal

birth weight (3,000–3,500 g). The authors explained these results in the context

of IIH suggesting that the compromised conditions of mothers’ growth pass on

similar risk for their offspring.

Intergenerational influences have also been tested for body composition

in Maya populations. A study by Wilson et al (2014) aimed to determine whether

mothers’ adult height (used as an indicator of early life environment) had an

intergenerational influence on several adiposity parameters of their children.

The sample included Maya children (7-9 years of age) and their mothers. In

general mothers exhibited very low heights (mean = 146.84 cm, SD = 4.58 cm)

and children high levels of body fat (mean = 28.40%, SD = 6.81%). After

controlling for sanitation index of the family and maternal parity, maternal height

did not predict significantly the children´s BMI, waist circumference and

percentage body fat, which suggest that recent environment and lifestyles are

more relevant than the intergenerational legacy in this sample.

Our results suggest that the grandmothers’ house type is a good

indicator of environmental quality during their growing years. We suggest that

grandmothers who lived in a house type which was built with durable materials

(e.g., cement) belonged to families who experienced in general the best living

conditions relative to other families. The next best grandmaternal house type

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was found to be the Maya type - palm leaf roof, wattle and daub walls and dirt

floor. Finally, grandmothers who grew up in a house built with perishable

materials (cardboard and corrugated metal) belonged to families who

experienced the most disadvantaged conditions, probably because these

families were in a transition period from traditional to modern conditions.

Larger grand-maternal family size was another intergenerational

predictor of greater children’s linear growth. This finding makes sense in the

context of the demographic characteristics of rural societies, such as the Maya,

who depended on agricultural activities for subsistence. These rural societies

took advantage of larger family size to increase their economic productivity.

Ethnographic evidence for this is provided by Kramer (2005) who studied

Xculoc, a Maya farming village in the Yucatan. Kramer describes how family

size and the presence of offspring at home until 25 years of age contribute

significantly to increase the production of maize and other benefits for the

family. Maya families of Xculoc had, on average, 7 children and the presence of

grandparents at home was very common. Kramer also found that children were

assigned childcare activities and domestic chores from around three years of

age and then were involved in the laborious tasks of harvesting and transporting

the maize. Domestic work and childcare were gender-based, with females

allocating more time to these activities.

In our study 74% of the grandmothers reported that their fathers worked

for the most part of their lives in the milpa, a complex form of swidden

agriculture involving about 40 vegetal species (Tuxill et al., 2010). On average,

grandmothers’ family size was 8 and the number of their own offspring was 7.

Therefore we hypothesize that those grandmothers belonging to bigger families

experienced better conditions during growth, which in turn have positive

intergenerational impacts on the growth of their grandchildren.

The effect of grand-maternal home type and family size was more

evident on children’s LL than in total height. A growing body of research finds

that the leg, especially the tibia, is more sensitive to intergenerational influences

than total height (reviewed by Bogin & Varela-Silva 2010).

The biological condition shown by the Maya participating in the present

study, as well as our previous research articles, reveals the effects of chronic

deprivation along several generations. Our results suggest that early

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environments experienced by mothers and grandmothers impacted negatively

their own growth and have significant influences on their descendants’ growth

trajectories. The processes through which intergenerational influences operate

have been not completely elucidated. However, gestation seems to be a key

period which triggers complex biological processes, including epigenetic

modifications that help to explain some phenotypic traits and conditions in

individuals. Evidence suggests that epigenetic marks are established during

early stages of embryogenesis and exhibit environmental plasticity into the

postnatal period (Gluckman et al., 2011). It has been suggested that maternal

nutrients and hormones act as cues of environmental conditions which allow

offspring to adjust their growth and development (Gluckman and Hanson, 2005)

in utero. The exposure to hormones can induce durable epigenetic

modifications that potentially modify the offspring’s physiology, metabolism and

functions during postnatal stages (Kuzawa and Thayer, 2011).

Accumulated evidence suggests that offspring biology is possibly less

sensitive to rapid changes in the current environment when adverse

intergenerational influences or signals are present. For instance, some studies

of nutritional interventions during pregnancy have shown little or moderate

impacts on the offspring development (Villar et al., 2007; Kramer and Kakuma,

2010). In contrast, larger effects have been found when nutritional interventions

have been done prior to pregnancy (Stein et al., 2003; Behrman et al., 2009).

Understanding the timescale at which intergenerational influences operate is

particularly important if we are interested in implementing effective interventions

to improve the nutritional and health status of the current and future

generations. Even if well planned interventions are implemented in populations

with long histories of deprivation and poverty, then positive results may require

two or more generations to be detected (Kuzawa and Tahyer, 2011; Bogin

2013).

We hypothesise that Maya people will not overcome the negative

intergenerational influences unless poverty levels are not substantially reduced.

According to official reports, by 2010, 46.2% (52 million) of the Mexican

population was classified as poor (CONEVAL, 2013). As in many other regions

of the world, poverty in Mexico tends to be more severe in indigenous groups,

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including the Maya, and this situation has been reflected in the biological

condition of indigenous Mexicans (Rivera-Domarco et al., 2013).

Historically, the south-east of Mexico has shown greater economic

poverty levels than the centre and the north of the country. The magnitude of

the problem is so great that despite the increase in social assistance programs

for indigenous communities in the last few years their net effect remain still

insufficient (INSP-SSP, 2007; INSP, 2013). In addition, the Yucatan has

remained in the last fifteen years among the states with the highest rates of

social inequality, measured as the concentration of the highest income

disparities (CONEVAL, 2014). We believe that reducing the poverty levels in

Mexico necessarily implies to reduce the levels of social inequality through a

more equitably wealth distribution.

ACKNOWLEDGMENTS

The authors would like to thank again the people who participated in the field

work of this research, especially to Biol. Graciela Valentin, research assistant of

Cinvestav and the students of nutrition Frida Gutierrez and Paulina Cauich. The

MSc. Ina Lopez generated the dataset and participated in the design of the

recruitment of participants. We also would like to thank the mothers,

grandmothers and children who accepted to participate in the study.

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Table 1 Intergenerational effects on children z-score values for height

Model 1 Model 2 Model 3

B (SE) p B (SE) p B (SE) p CI 95%

Maternal z-score of height 0.419 (0.093) <0.001 0.401 (0.093) <0.001 0.416 (0.094) <0.001 0.23 0.60

Paternal job loss during maternal childhood -0.317 (0.192) 0.103 -0.176 (0.187) 0.350 -0.55 0.20

Grandmaternal short height -0.271 (0.221) 0.221 -0.71 0.17

Grandmaternal home index (reference = household Maya typea)

-Perishable materials (cardboard & metal) -0.439 (0.154) 0.005 -0.74 -0.13

-Durable material (cement) 0.412 (0.321) 0.203 -0.22 1.05

Grandmaternal family size during childhood 0.043 (0.023) 0.061 0.00 0.09

Constant 0.180 (0.200) 0.371 0.192 (0.199) 0.338 0.189 (0.323) 0.559 -0.45 0.83

R2 adjusted 0.151 0.164 0.248 aHousehold Maya type: palm leaf roof, wattle & daub walls and ground floor; S.E.: standard error; n = 109, F (6, 102) = 6.95, p<0.001, R

2 = 0.290; Shapiro-

Wilk residual normality test: w = 0.98, p = 0.126; Breusch-Pagan/Cook-Weisberg homoscedasticity test: X2(1) = 0.04, p = 0.840.

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Table 2 Intergenerational effects on children z-score values for leg length

Model 1 Model 2 Model 3

B (SE) p B (SE) p B (SE) p CI 95%

Maternal z-score of LL 0.369 (0.094) <0.001 0.352 (0.093) <0.001 0.353 (0.083) <0.001 0.19 0.52

Paternal job loss during maternal childhood -0.381 (0.220) 0.086 -0.093 (0.192) 0.630 -0.47 0.29

Grandmaternal short height -0.040 (0.224) 0.859 -0.48 0.40

Grandmaternal home index (reference = household Maya typea)

-Perishable materials (cardboard & metal) -0.533 (0.155) 0.001 -0.84 -0.23

-Durable material (cement) 0.623 (0.326) 0.059 -0.02 1.27

Grandmaternal family size 0.073 (0.023) 0.002 0.03 0.12

Constant -0.498 (0.178) 0.006 -0.476 (0.177) 0.010 -0.767 (0.351) 0.031 -1.51 -0.28

R2 adjusted 0.118 0.135 0.297 aHousehold Maya type: palm leaf roof, wattle & daub walls and ground floor; S.E.: standard error; n = 106, F (6, 99) = 8.38, p<0.001, R

2 = 0.337; Shapiro-Wilk

residual normality test: w = 0.99, p = 0.693; Breusch-Pagan/Cook-Weisberg homoscedasticity test: X2(1) = 0.19, p = 0.659

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Azcorra Et Al Intergenerational Influences on Maya